ebook img

The Dark Triad and HEXACO Model of Personality in Relational Aggression PDF

92 Pages·2016·1.21 MB·English
by  
Save to my drive
Quick download
Download
Most books are stored in the elastic cloud where traffic is expensive. For this reason, we have a limit on daily download.

Preview The Dark Triad and HEXACO Model of Personality in Relational Aggression

TThhee UUnniivveerrssiittyy ooff SSoouutthheerrnn MMiissssiissssiippppii TThhee AAqquuiillaa DDiiggiittaall CCoommmmuunniittyy Master's Theses Spring 5-2016 TThhee DDaarrkk TTrriiaadd aanndd HHEEXXAACCOO MMooddeell ooff PPeerrssoonnaalliittyy iinn RReellaattiioonnaall AAggggrreessssiioonn Niki M. Knight University of Southern Mississippi Follow this and additional works at: https://aquila.usm.edu/masters_theses Part of the Clinical Psychology Commons, Counseling Psychology Commons, Other Psychology Commons, Personality and Social Contexts Commons, School Psychology Commons, and the Social Psychology Commons RReeccoommmmeennddeedd CCiittaattiioonn Knight, Niki M., "The Dark Triad and HEXACO Model of Personality in Relational Aggression" (2016). Master's Theses. 164. https://aquila.usm.edu/masters_theses/164 This Masters Thesis is brought to you for free and open access by The Aquila Digital Community. It has been accepted for inclusion in Master's Theses by an authorized administrator of The Aquila Digital Community. For more information, please contact [email protected]. THE DARK TRIAD AND HEXACO PERSONALITY MODEL IN RELATIONAL AGGRESSION by Niki Marie Knight A Thesis Submitted to the Graduate School and the Department of Psychology at The University of Southern Mississippi in Partial Fulfillment of the Requirements for the Degree of Master of Arts Approved: ________________________________________________ Dr. Eric R. Dahlen, Committee Chair Associate Professor, Psychology ________________________________________________ Dr. Emily B. Yowell, Committee Member Associate Professor, Psychology ________________________________________________ Dr. Michael B. Madson, Committee Member Associate Professor, Psychology ________________________________________________ Dr. Karen S. Coats Dean of the Graduate School May 2016 ABSTRACT THE DARK TRIAD AND HEXACO MODEL OF PERSONALITY IN RELATIONAL AGGRESSION by Niki Marie Knight May 2016 Past research has linked relational aggression (RA) to many forms of psychological maladjustment among children and early adolescents. Although less is known about RA among emerging adults, there is a growing body of research demonstrating a number of adverse correlates. This literature has sparked an interest in examining the role of personality in RA. Most investigations to date have focused on the Five Factor Model; however, the six factor HEXACO model of personality (Ashton et al., 2004) may offer some advantages in studying RA. Moreover, the manipulative and often covert nature of RA among emerging adults has theoretical overlap with the “Dark Triad” of personality (i.e., psychopathy, narcissism, and Machiavellianism). This study explored the utility of the HEXACO model and the Dark Triad constructs in predicting proactive and reactive RA among college students. Hierarchical multiple regression was used to test the predictive utility of these constructs and assess the potential role of gender. Participants low in Honesty-Humility and Agreeableness reported utilizing more proactive and reactive RA. All three Dark Triad traits were positive predictors of reactive RA; narcissistic and psychopathic traits were positive predictors of proactive RA. Although there was some evidence that respondent gender moderated the relationships between certain independent variables and RA in regression models that included all predictive constructs, these effects were not evident when these variables were examined in isolation. The findings suggest that ii the HEXACO model of personality and the Dark Triad traits have utility in understanding relational aggression among emerging adults. iii ACKNOWLEDGMENTS Special thanks goes to my committee director, Dr. Eric Dahlen, and my other committee members, Dr. Emily Yowell and Dr. Michael Madson, for their advice and support throughout the duration of this research. iv TABLE OF CONTENTS ABSTRACT………………………………………………………………………………ii ACKNOWLEDGMENTS………………………………………………………………..iv LIST OF TABLES……………………………………………………………………….vi CHAPTER I. INTRODUCTION………………………………………………………...1 Models of General Personality Structure The Dark Triad The Present Study II. METHOD………………………………………………………………..13 Participants Instruments Procedure Statistical Analyses III. RESULTS………………………………………………………………..21 Data Clean-Up and Preliminary Analyses Primary Analyses Exploratory Analyses IV. DISCUSSION……………………………………………………………40 Relational Aggression and the HEXACO Personality Model The Dark Triad and Relational Aggression Limitations and Future Directions APPENDIXES…………………………………………………………………………...53 REFERENCES…………………………………………………………………………..70 v LIST OF TABLES Table 1. Scale Reliabilities, Means, Standard Deviations, and Gender Differences ............... 22 2. Intercorrelations of Variables .................................................................................... 23 3. Hierarchical Regression Analysis Summary for Honesty-Humility and Agreeableness Predicting Reactive Relational Aggression ....................................... 25 4. Hierarchical Regression Analysis Summary for Honesty-Humility and Agreeableness Predicting Proactive Relational Aggression ...................................... 26 5. Hierarchical Regression Analysis Summary for the PNI, SRP-III, and MACH-IV Predicting Reactive Relational Aggression ............................................................... 27 6. Hierarchical Regression Analysis Summary for the PNI, SRP-III, and MACH-IV Predicting Proactive Relational Aggression .............................................................. 28 7. Hierarchical Regression Analysis Summary for Honesty-Humility, PNI, SRP-III and MACH-IV Predicting Reactive Relational Aggression ............................................. 30 8. Hierarchical Regression Analysis Summary for Honesty-Humility, PNI, SRP-III and MACH-IV Predicting Reactive Relational Aggression ............................................. 32 9. Scale Reliabilities, Means, Standard Deviations, and Gender Differences ............... 34 10. Correlations of the HEXACO, PNI, NPI, MACH-IV, and SRP-III Scales With Raw and Residualized Proactive and Reactive Relational Aggression .............................. 36 vi CHAPTER I INTRODUCTION Relational aggression (RA) is a form of aggressive behavior that involves damaging the social standing or relationships of the victim through socially manipulative avenues, using the relationship as a vehicle of harm (Crick, 1996; Crick & Grotpeter, 1995; Ellis, Crooks, & Wolfe, 2009; Werner & Crick, 1999). Examples of RA include threats to withdraw friendship, intentional ignoring, group exclusion, and rumor spreading (Fite, Stoppelbein, Greening & Preddy, 2011; Werner & Crick, 1999). Among children and early adolescents, RA has been linked to social problems, peer rejection, depression, suicidal ideation, poor academic performance, and frustration (Fite et al., 2011; Ojanen, Findley, & Fuller, 2012; Preddy & Fite, 2012). Furthermore, adolescent self-reports of relational aggression predicted delinquency and risk-taking (Spieker et al., 2011). While much of the research on RA has been conducted with children and early adolescents, there is evidence that RA has a number of adverse correlates among older adolescents and emerging adults. Examples include anxiety, depression, self-harm, substance use, poor impulse control and anger regulation, disordered eating, maladaptive personality traits, peer rejection, and adjustment difficulties (Linder, Crick, & Collins, 2002; Miller & Lynam, 2003; Ostrov & Houston, 2008; Storch, Werner, & Storch, 2003; Werner & Crick, 1999). In a recent study by Dahlen, Czar, Prather, and Dyess (2013), general/peer RA was associated with anxiety, depression, loneliness, stress, trait anger, academic burnout, and the misuse of alcohol in a college sample. After controlling for 1 respondent gender, race, and relational victimization, Dahlen and colleagues found that anxiety, trait anger, and alcohol misuse predicted general/peer RA. In addition to the two forms of aggressive behavior (i.e., overt and relational), aggression can be separated by function into proactive and reactive aggression (Burton, Hafetin, & Hanninger, 2007; Murray-Close, Ostrov, Nelson, Crick, & Coccaro, 2010; Ostrov & Houston, 2008). Proactive RA is planned and has a goal-directed end (e.g., spreading rumors to make oneself more popular). Reactive RA is impulsive and done out of anger, usually in retaliation for a perceived insult (e.g., spreading malicious rumors about a peer after having been insulted by that peer). The distinction can be useful because there is some evidence that proactive and reactive RA have different correlates. For example, Murray-Close and colleagues (2010) found that reactive RA but not proactive RA correlated with distress experienced in provocative relational contexts, hostile attributions, and abuse history. Moreover, the relationships of reactive RA to measures of anger and hostility were stronger than those for proactive RA. In spite of the adverse interpersonal correlates of RA, it should be recognized that RA does require some level of status in one’s peer group because most acts of RA require the cooperation of others. For example, a malicious rumor one starts will have little effect unless others are willing to help spread it, and one cannot effectively exclude someone from one’s social circle unless the other members agree to it. Thus, RA seems to require at least some ability to be cooperative and friendly around others in order to have the support needed to engage in these behaviors. It has been suggested that RA is most likely to occur when these prosocial skills are paired with a lack of empathy in social interactions (Ojanen et al., 2012). Lack of empathy, the desire to manipulate 2 others, and/or the conviction that one is entitled to punish those who deviate from one’s expectations may facilitate RA and can be found in certain personality constructs that may be useful predictors of RA. Models of General Personality Structure The Five Factor Model (FFM) of personality (Costa & McCrae, 1992; Goldberg, 1990) has been used extensively to provide a broad representation of human personality, and this has proven useful in understanding how personality is associated with overt and relational forms of aggression (Burton et al., 2007; Egan & Lewis, 2011; Hines & Saudino, 2008; Jones, Miller, & Lynam, 2011; Miller & Lynam, 2001, 2006; Miller, Zeichner, & Wilson, 2012). Using a sample of community adults, Egan and Lewis (2011) found that Neuroticism was positively related to overt affective aggression and both Agreeableness and Extraversion were inversely related to overt narcissistic aggression. They also found that some of the relationships between the FFM domains and overt aggression varied by respondent gender. Specifically, the inverse relationships of Agreeableness and Extraversion to narcissistic aggression were stronger for men than for women. Hines and Saudino (2008) found that Neuroticism was positively related to psychological aggression, a construct similar to RA, for both male and female college students but that psychological aggression was positively related to Conscientiousness and inversely related to Agreeableness among women. Miller and colleagues (2012) found that RA was inversely related to both Agreeableness and Conscientiousness and was positively related to Neuroticism among college students. Burton and colleagues (2007), also using a college sample, found that the relationships between FFM domains and RA varied by respondent gender (i.e., Agreeableness was inversely related to RA for 3

Description:
Grandiosity and Narcissistic Vulnerability) were used in the analyses to test our . transformed with a logarithmic transformation to reduce skewness.
See more

The list of books you might like

Most books are stored in the elastic cloud where traffic is expensive. For this reason, we have a limit on daily download.